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    Russell Jurney

    Russell Jurney (He/Him)

    Former early LinkedIn / Ning / Hortonworks seeks leadership role in AI Engineering startup. Deep AI engineering expertise in knowledge graphs, entity resolution

    Entrepreneur New York City Georgia State University
    oreilly.com
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    Experience
    Graphlet AI
    Graphlet AI
    Consultant 2022 - Present (over 4 years)
    Consultant. Building a Knowledge Graph Factory, a platform as "wizard" for efficiently building knowledge graphs, automating tasks with graph ML and serving the results. We... more are technology consultants focused on knowledge graphs, Graph Neural Networks, natural language processing, search and graph databases.

    In open source at: https://github.com/Graphlet-AI/graphlet
    Deep Discovery
    Deep Discovery
    Founder, CTO 2020 - 2022 (over 1 year)
    I was Co-Founder and CTO and led the development of a system for Know Your Customer (KYC) checks that visualized a customers' risk in terms of their network of business associations.

    The... more accomplishments I am most proud of are:

    * Built and managed a passionate team of 25 amazing people
    * Built a 3 billion node business graph with a uniform ontology out of half a dozen datasets
    * Entity resolved its entities 5:1 via with a model we invented called DeepEM that incorporates deep embeddings for fuzzy matching as well as network topology and includes a highly scalable blocking methodology
    * Built an explainable risk score based on supervised graph ML of known criminals and their networks
    * Built an unsupervised risk score using motif-based learning I personally developed
    * Designed and built a user interface visualizing the risk scores of an entity and its local network
    * Designed and built a rich graph search engine over all 3 billion input companies and their officers
    * Built an information extraction of adverse media and entity linked new criminals into our business graph
    Stealth Search Startup
    Stealth Search Startup
    Founding CTO 2020 (7 months)
    Founding CTO for a seed stage developer tools startup building a domain-specific search engine that used a graph neural network (GNN) model of an online community to power... more a contextual search engine. Helped raise series A. Solr, Elastic, Tensorflow, sentence transformers, PyTorch, NLP, vector search.

    Left due to Covid-related illness, since recovered.
    Data Syndrome
    Data Syndrome
    Principal Consultant 2012 - 2019 (almost 8 years)
    Consultant specializing in shipping full-stack analytics products from conception to deployment. Developed several recommender systems, dev ops/data engineering for products,... more lead generation systems, machine learning products.

    For six months, I served as acting CTO at a developer tools company working on a graph neural network (GNN) model of the open-source ecosystem to drive contextual, vector search to crack difficult code search problems.
    Relato
    Relato
    Founder, Founder 2015 - 2016 (almost 2 years)
    Founder of Relato which performed graph analytics on its own acquired copy of the business graph to power company recommendations and market visualizations.
    E8 Security
    E8 Security
    Principal Data Scientist 2014 (9 months)
    Nine month data scientist in residence period in which I jump started the full-stack product from zero code to a working application that was the basis for a seed round. E8... more went on to raise a series B, and was acquired by Cisco.
    LinkedIn
    Exit
    LinkedIn
    Senior Data Scientist 2010 - 2011 (over 1 year)
    Shipped two apps in a year: Career Explorer, LinkedIn InMaps. Launched and shipped proof of concept for JRuby initiative, which the CTO characterized as "the most important... more project in LinkedIn's history."

    Job cut short by recovery from car accident.
    Ning
    Exit
    Ning
    Visualization Engineer 2009 - 2010 (5 months)
    Created interactive dashboards, worked directly for CEO investigating and resolving key growth problems, managed data science team.
    Lucision
    Lucision
    Founder 2005 - 2008 (over 2 years)
    Developed an interactive web based visualization system for slot machines in the casino gaming industry. Performed all product functions from conception through development... more through sales and marketing.
    Founder
    Relato
    Employee
    Ning, LinkedIn, Lucision, E8 Security, Data Syndrome, Stealth Search Startup, Deep Discovery, Graphlet AI
    Investor
     
    Incubator
     
    Advisor
     
    Attorney
     
    Board Member
     
    Mentor
     
    Member
     
    Acquired
     
     
    Projects
    Agile Data Science 2.0
    Author of 2nd ed book to pioneer agile data science method
    Author, Apache Spark, Javascript, Python · Data science teams looking to turn research into useful analytics applications require not only the right… · More tools, but also the right approach if they're to succeed. With the revised second edition of this hands-on guide, up-and-coming data scientists will learn how to use the Agile Data Scie...

    Data science teams looking to turn research into useful analytics applications require not only the right tools, but also the right approach if they’re to succeed. With the revised second edition of this hands-on guide, up-and-coming data scientists will learn how to use the Agile Data Science development methodology to build data applications with Python, Apache Spark, Kafka, and other tools.

    Author Russell Jurney demonstrates how to compose a data platform for building, deploying, and refining analytics applications with Apache Kafka, MongoDB, ElasticSearch, d3.js, scikit-learn, and Apache Airflow. You’ll learn an iterative approach that lets you quickly change the kind of analysis you’re doing, depending on what the data is telling you. Publish data science work as a web application, and affect meaningful change in your organization.

    * Build value from your data in a series of agile sprints, using the data-value pyramid
    * Extract features for statistical models from a single dataset
    * Visualize data with charts, and expose different aspects through interactive reports
    * Use historical data to predict the future via classification and regression
    * Translate predictions into actions
    * Get feedback from users after each sprint to keep your project on track
    LinkedIn InMaps
    Lead data scientist/engineer and product manager for project
    Lead Developer, Product Manager · InMaps was a cutting edge visualization of your LInkedIn network. It is the largest interactive network visualization ever created.
    Mapping Big Data
    First data-driven market report on the Big Data space
    Author · This report will analyze the "big data" market space, using social network analysis (SNA) of the network of partnerships among… · More vendors. It's the first of its kind-this market report is entirely data driven. In this report, we collect data from the Web, analyze it to produce insight, and interpret insight to produce market intelligence.

    To discover the shape and structure of the big data market, the San Francisco-based startup Relato took a unique approach to market research and created the first fully data-driven market report. Company CEO Russell Jurney and his team collected and analyzed raw data from a variety of sources to reveal a boatload of business insights about the big data space. This exceptional report is now available for free download.

    Using data analytic techniques such as social network analysis (SNA), Relato exposed the vast and complex partnership network that exists among tens of thousands of unique big data vendors. The dataset Relato collected is centered around Cloudera, Hortonworks, and MapR, the major platform vendors of Hadoop, the primary force behind this market.

    From this snowball sample, a 2-hop network, the Relato team was able to answer several questions, including:

    * Who are the major players in the big data market?
    * Which is the leading Hadoop vendor?
    * What sectors are included in this market and how do they relate?
    * Which among the thousands of partnerships are most important?
    * Who’s doing business with whom?
    * Metrics used in this report are also visible in Relato’s interactive web application, via a link in the report, which walks you through the insights step-by-step.
    Career Explorer
    Lead data scientist developing career simulation engine
    Lead Data Scientist · We're excited to launch our latest beta product: LinkedIn's Career Explorer. Students now have the ability to explore… · More different career paths based on their school, level of education, and desired industry. In addition to visualizing various career paths, they'll also be able to find relevant job opp
    Agile Data Science
    Author of 1st book on theory/practice of agile data science
    Author, Apache Hadoop, Apache Pig, Python · Mining big data requires a deep investment in people and time. How can you be sure you're building the… · More right models? With this hands-on book, you'll learn a flexible toolset and methodology for building effective analytics applications...

    Mining big data requires a deep investment in people and time. How can you be sure you’re building the right models? With this hands-on book, you’ll learn a flexible toolset and methodology for building effective analytics applications with Hadoop.

    Using lightweight tools such as Python, Apache Pig, and the D3.js library, your team will create an agile environment for exploring data, starting with an example application to mine your own email inboxes. You’ll learn an iterative approach that enables you to quickly change the kind of analysis you’re doing, depending on what the data is telling you. All example code in this book is available as working Heroku apps.

    * Create analytics applications by using the agile big data development methodology
    * Build value from your data in a series of agile sprints, using the data-value stack
    * Gain insight by using several data structures to extract multiple features from a single dataset
    * Visualize data with charts, and expose different aspects through interactive reports
    * Use historical data to predict the future, and translate predictions into action
    * Get feedback from users after each sprint to keep your project on track
    Committer, Apache DataFu
    Added NLP and other features to Apache Pig library
    Apache DataFu Hourglass is a library for incrementally processing data using Hadoop MapReduce. This library was inspired by the prevalance of sliding window… · More computations over daily tracking data at LinkedIn. Computations such as these typically happen at regular intervals (e.g. daily, weekly), and therefore the sliding nature of the computations means that much of the work is unnecessarily repeated.
    Big Data for Chimps
    Book on data flow programming using Apache Hadoop/Pig
    Co-Author, Apache Hadoop, Apache Pig, Python · Finding patterns in massive event streams can be difficult, but learning how to find them doesn’t have… · More to be. This unique hands-on guide shows you how to solve this and many other problems in large-scale data processing with simple, fun, and elegant tools that leverage Apache Hadoop. You’ll gain a practical, actionable view of big data by working with real data and real problems.

    Perfect for beginners, this book’s approach will also appeal to experienced practitioners who want to brush up on their skills. Part I explains how Hadoop and MapReduce work, while Part II covers many analytic patterns you can use to process any data. As you work through several exercises, you’ll also learn how to use Apache Pig to process data.

    Finding patterns in massive event streams can be difficult, but learning how to find them doesn't have to be. This unique hands-on guide shows you how to solve this and many other problems in large-scale data processing with simple, fun, and...
    Philip (flip) Kromer
    With Philip (flip) Kromer
     
    Education
     
    About
    Achievements

    Wrote 4 O'Reilly books: Agile Big Data, Big Data for Chimps, Agile Data Science 2.0, Mapping Big Data.

    Patent: Methods and systems for exploring career options, US20120226623 A1

    LinkedIn: shipped Career Explorer and LinkedIn InMaps in 8 months

    Describe the most impressive thing you've done.
    Skills
    Artificial Intelligence Machine Learning Natural Language Processing Predictive Analytics Exploratory Data Analysis Agile Amazon Web Services Application Development Architect Consulting Distributed Systems Infrastructure Management Product Development Research Web Development Deep Learning Google Cloud Platform Analytics Python Dev Ops Social Networking Product Management Applied Research Apache Spark Information Retrieval Software Engineering Data Science Data Engineering Start-Ups D3.js Data Visualization Graphs Neural Networks ElasticSearch Apache Hadoop Bash Engineering Java Javascript Statistics Cloud Computing Apache/Spark/Databricks Data Visualization (Matplotlib, Seaborn, Bokeh) Data Analysis NLP Business Intelligence Machine Learning Data Science Python GNN PyTorch TensorFlow Neo4J TigerGraph GSQL Gremlin AWS GCP Google Cloud Platform (GCP) Amazon Elastic MapReduce OpenSearch Scala Machine Learning Data Science Python R TypeScript Statistical Analysis Probability & Statistics Generative AI Large Language Models (LLMs) Spark Hadoop/Hive/Spark/Scala/MLlib PySpark (Core Spark and Spark SQL) Cypher FastAPI
    Locations
    San Francisco Oakland Berkeley Palo Alto Mountain View San Mateo
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